Salient’s AI-based forecasting model solves weather prediction challenges

AI-powered S2S model delivers new breakthrough levels of reliability and predictability in long-range weather forecasts

Salient Predictions, a leading pioneer in weather forecasting analytics, is adapting to increasing climate volatility by setting new standards in long-range weather prediction with a major upgrade to its revolutionary forecasting solution, the sub-seasonal-to-seasonal (S2S) model, to deliver forecasts two to 52 weeks in advance. Developed by a leading team of scientists and engineers, the cutting-edge AI model employs the power of AI and calibration to create reliable probabilistic distributions and empower decision-makers to navigate weather-related challenges and opportunities with greater confidence. 

“Global climate change is spurring volatile weather patterns around the world,” said Matt Stein, co-founder and CEO of Salient. “This is presenting urgent challenges in weather forecasting and analytics. A substantial upgrade to our S2S model and a breakthrough for the industry, this release addresses these pressing issues, delivering major improvements in temperature, precipitation, and other forecasting variables. Salient’s new forecasting model stands out for its exceptional accuracy and reliability with new capabilities that enable confident decisions with long-range forecasts amidst unprecedented weather patterns.”

In the face of pressing global warming challenges, the new S2S model provides indispensable tools to address climate-related risks and vulnerabilities. The accuracy improvements for temperature and precipitation outperform benchmark models such as NOAA’s Global Ensemble Forecast System (GEFS), European Centre for Medium-Range Weather Forecasts (ECMWF), and climatology. Accuracy excels in sub-seasonal weekly forecasts, enhancing its value in critical decision-making scenarios for commodity trading, agronomic decisions, renewable energy production, and more. Based on a comparison of the Continuous Ranked Probability Score (CRPS) to reference models, the accuracy gain can reach up to 50 per cent.

With its reliable probabilistic forecasts, the new model better equips stakeholders across various sectors from agriculture, energy, finance, and beyond with the knowledge to mitigate the impact of extreme weather events, optimise resource management, and prioritise climate adaptation strategies.

AI-powered S2S model delivers new breakthrough levels